OpenRaiser/Intern-Atlas huggingface dataset:
Eine entscheidbare Klasse n-stelliger Horn-Prädikate
Venue: arXiv cs.LO 2014
Year: 2014

Similar to a tree grammar, a Horn theory can be used to describe an infinite set of terms. In this paper, we present a class of Horn theories such that the set of definable predicates is closed wrt. conjunction and such that the satisfiability of a predicate is decidable. This extends previous results on Horn clauses with unary predicates.
Capturing Aggregate Flexibility in Demand Response
Venue: arXiv cs.SY 2014
Year: 2014

Flexibility in electric power consumption can be leveraged by Demand Response (DR) programs. The goal of this paper is to systematically capture the inherent aggregate flexibility of a population of appliances. We do so by clustering individual loads based on their characteristics and service constraints. We highlight the challenges associated with learning the customer response to economic incentives while applying demand side management to heterogeneous appliances. We also develop a framework to quantify customer privacy in direct load scheduling programs.
Towards Automating the Construction & Maintenance of Attack Trees: a Feasibility Study
Venue: arXiv cs.CR 2014
Year: 2014

Security risk management can be applied on well-defined or existing systems; in this case, the objective is to identify existing vulnerabilities, assess the risks and provide for the adequate countermeasures. Security risk management can also be applied very early in the system's development life-cycle, when its architecture is still poorly defined; in this case, the objective is to positively influence the design work so as to produce a secure architecture from the start. The latter work is made difficult by the uncertainties on the architecture and the multiple round-trips required to keep the risk assessment study and the system architecture aligned. This is particularly true for very large projects running over many years. This paper addresses the issues raised by those risk assessment studies performed early in the system's development life-cycle. Based on industrial experience, it asserts that attack trees can help solve the human cognitive scalability issue related to securing those large, continuously-changing system-designs. However, big attack trees are difficult to build, and even more difficult to maintain. This paper therefore proposes a systematic approach to automate the construction and maintenance of such big attack trees, based on the system's operational and logical architectures, the system's traditional risk assessment study and a security knowledge database.
Visual and Predictive Analytics on Singapore News: Experiments on GDELT, Wikipedia, and ^STI
Venue: arXiv cs.OH 2014
Year: 2014

The open-source Global Database of Events, Language, and Tone (GDELT) is the most comprehensive and updated Big Data source of important terms extracted from international news articles . We focus only on GDELT's Singapore events to better understand the data quality of its news articles, accuracy of its term extraction, and potential for prediction. To test news completeness and validity, we visually compared GDELT (Singapore news articles' terms from 1979 to 2013) to Wikipedia's timeline of Singaporean history. To test term extraction accuracy, we visually compared GDELT (CAMEO codes and TABARI system of extraction from Singapore news articles' text from April to December 2013) to SAS Text Miner's term and topic extraction. To perform predictive analytics, we propose a novel feature engineering method to transform row-level GDELT from articles to a user-specified temporal resolution. For example, we apply a decision tree using daily counts of feature values from GDELT to predict Singapore stock market's Straits Times Index (^STI). Of practical interest from the above results is SAS Visual Analytics' ability to highlight the various impacts of June 2013 Southeast Asian haze and December 2013 Little India riot on Singapore. Although Singapore is unique as a sovereign city-state, a leading financial centre, has strong international influence, and consists of a highly multi-cultural population, the visual and predictive analytics reported here are highly applicable to another country's GDELT data.
Automatic Tracker Selection w.r.t Object Detection Performance
Venue: arXiv cs.CV 2014
Year: 2014

The tracking algorithm performance depends on video content. This paper presents a new multi-object tracking approach which is able to cope with video content variations. First the object detection is improved using Kanade- Lucas-Tomasi (KLT) feature tracking. Second, for each mobile object, an appropriate tracker is selected among a KLT-based tracker and a discriminative appearance-based tracker. This selection is supported by an online tracking evaluation. The approach has been experimented on three public video datasets. The experimental results show a better performance of the proposed approach compared to recent state of the art trackers.
Optimizing The Selection of Strangers To Answer Questions in Social Media
Venue: arXiv cs.SI 2014
Year: 2014

Millions of people express themselves on public social media, such as Twitter. Through their posts, these people may reveal themselves as potentially valuable sources of information. For example, real-time information about an event might be collected through asking questions of people who tweet about being at the event location. In this paper, we explore how to model and select users to target with questions so as to improve answering performance while managing the load on people who must be asked. We first present a feature-based model that leverages users exhibited social behavior, including the content of their tweets and social interactions, to characterize their willingness and readiness to respond to questions on Twitter. We then use the model to predict the likelihood for people to answer questions. To support real-world information collection applications, we present an optimization-based approach that selects a proper set of strangers to answer questions while achieving a set of application-dependent objectives, such as achieving a desired number of answers and minimizing the number of questions to be sent. Our cross-validation experiments using multiple real-world data sets demonstrate the effectiveness of our work.
Efficiency of conformalized ridge regression
Venue: arXiv cs.LG 2014
Year: 2014

Conformal prediction is a method of producing prediction sets that can be applied on top of a wide range of prediction algorithms. The method has a guaranteed coverage probability under the standard IID assumption regardless of whether the assumptions (often considerably more restrictive) of the underlying algorithm are satisfied. However, for the method to be really useful it is desirable that in the case where the assumptions of the underlying algorithm are satisfied, the conformal predictor loses little in efficiency as compared with the underlying algorithm (whereas being a conformal predictor, it has the stronger guarantee of validity). In this paper we explore the degree to which this additional requirement of efficiency is satisfied in the case of Bayesian ridge regression; we find that asymptotically conformal prediction sets differ little from ridge regression prediction intervals when the standard Bayesian assumptions are satisfied.
Employing Virtualization for Information Technology Education
Venue: arXiv cs.CY 2014
Year: 2014

This manuscript presents teaching and curriculum design for Information Technology classes. Today, students demand hands-on activities for the newest technologies. It is feasible to satisfy this appetite for exciting education by employing server virtualization technologies to teach advanced concepts with extensive hands-on assignments. Through utilization of virtualized servers, students are able to deploy, secure and manage virtual machines and networks in a contained environment. Various techniques, assessment tools and experiences will be analyzed and presented by this manuscript. Previous teaching cases for Information Systems or Information Technology classes are done using non-commercial products, such as free VMware Server or VMware Player. Such products have very limited functionality in terms of networking, storage and resource management. Several advanced datacenter functions, such as Distributed Power Management (DPM), vMotion and others, are not available in desktop versions of that type of virtualization software. This manuscript introduces the utilization of commercial software, such as vSphere 4.1, with full datacenter functionality and operations for teaching Information Technology classes of various levels.
Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers
Venue: arXiv cs.RO 2014
Year: 2014

The success of the human-robot co-worker team in a flexible manufacturing environment where robots learn from demonstration heavily relies on the correct and safe operation of the robot. How this can be achieved is a challenge that requires addressing both technical as well as human-centric research questions. In this paper we discuss the state of the art in safety assurance, existing as well as emerging standards in this area, and the need for new approaches to safety assurance in the context of learning machines. We then focus on robotic learning from demonstration, the challenges these techniques pose to safety assurance and indicate opportunities to integrate safety considerations into algorithms "by design". Finally, from a human-centric perspective, we stipulate that, to achieve high levels of safety and ultimately trust, the robotic co-worker must meet the innate expectations of the humans it works with. It is our aim to stimulate a discussion focused on the safety aspects of human-in-the-loop robotics, and to foster multidisciplinary collaboration to address the research challenges identified.
Enhanced Cluster Computing Performance Through Proportional Fairness
Venue: arXiv cs.PF 2014
Year: 2014

The performance of cluster computing depends on how concurrent jobs share multiple data center resource types like CPU, RAM and disk storage. Recent research has discussed efficiency and fairness requirements and identified a number of desirable scheduling objectives including so-called dominant resource fairness (DRF). We argue here that proportional fairness (PF), long recognized as a desirable objective in sharing network bandwidth between ongoing flows, is preferable to DRF. The superiority of PF is manifest under the realistic modelling assumption that the population of jobs in progress is a stochastic process. In random traffic the strategy-proof property of DRF proves unimportant while PF is shown by analysis and simulation to offer a significantly better efficiency-fairness tradeoff.
Better Performance ACF Operation for PAPR Reduction of OFDM Signal
Venue: arXiv cs.NI 2014
Year: 2014

Orthogonal frequency division multiplexing (OFDM) is a promising modulation radio access scheme for next generation wireless communication systems because of its inherent immunity to multipath interference due to a low symbol rate, the use of a cyclic prefix, and its affinity to different transmission bandwidth arrangements. OFDM has already been adopted as a radio access scheme for several of the latest cellular system specifications such as the long-term evolution (LTE) system in the 3GPP (3rd Generation Partnership Project). Nevertheless, peak-to-average power ratio (PAPR) of OFDM signal is a significant drawback since it restricts the efficiency of the transmitter. A number of promising approaches have been proposed & implemented to reduce PAPR with the expense of increase transmit signal power, bit error rate (BER) & computational complexity and data rate loss, etc. In this paper, a relatively better scheme of amplitude clipping & filtering operation (ACF) is proposed and implemented which shows the significant improvement in case of PAPR reduction while increasing slight BER compare to an present method.
Efficient and Scalable Algorithms for Smoothed Particle Hydrodynamics on Hybrid Shared/Distributed-Memory Architectures
Venue: arXiv cs.DC 2014
Year: 2014

This paper describes a new fast and implicitly parallel approach to neighbour-finding in multi-resolution Smoothed Particle Hydrodynamics (SPH) simulations. This new approach is based on hierarchical cell decompositions and sorted interactions, within a task-based formulation. It is shown to be faster than traditional tree-based codes, and to scale better than domain decomposition-based approaches on hybrid shared/distributed-memory parallel architectures, e.g. clusters of multi-cores, achieving a $40\times$ speedup over the Gadget-2 simulation code.
Social Collaborative Retrieval
Venue: arXiv cs.IR 2014
Year: 2014

Socially-based recommendation systems have recently attracted significant interest, and a number of studies have shown that social information can dramatically improve a system's predictions of user interests. Meanwhile, there are now many potential applications that involve aspects of both recommendation and information retrieval, and the task of collaborative retrieval---a combination of these two traditional problems---has recently been introduced. Successful collaborative retrieval requires overcoming severe data sparsity, making additional sources of information, such as social graphs, particularly valuable. In this paper we propose a new model for collaborative retrieval, and show that our algorithm outperforms current state-of-the-art approaches by incorporating information from social networks. We also provide empirical analyses of the ways in which cultural interests propagate along a social graph using a real-world music dataset.
Analysis of Computer Hardware Affecting Video Transmission via IEEE 1394a connection
Venue: arXiv cs.MM 2014
Year: 2014

When 60 de-interlaced fields per second digital uncompressed video is streamed to a computer, some video fields are lost and not able to be stored on a computer s hard drive successfully. Additionally, this problem amplifies once multiple video sources are deployed. If it is possible to stream digital uncompressed video without dropped video fields, then a sophisticated computer analysis of the transmitted via IEEE 1394a connection video is possible. Such process is used in biomechanics when it is important to analyze athletes performance via streaming digital uncompressed video to a computer and then analyzing it. If a loss of video fields occurs, then a quality analysis of video is not possible.
The Secant-Newton Map is Optimal Among Contracting $n^{th}$ Degree Maps for $n^{th}$ Root Computation
Venue: arXiv cs.SC 2014
Year: 2014

Consider the problem: given a real number $x$ and an error bound $ε$, find an interval such that it contains the $\sqrt[n]{x}$ and its width is less than $ε$. One way to solve the problem is to start with an initial interval and to repeatedly update it by applying an interval refinement map on it until it becomes narrow enough. In this paper, we prove that the well known Secant-Newton map is optimal among a certain family of natural generalizations.
A Direct Approach to Computing Spatially Averaged Outage Probability
Venue: arXiv cs.IT 2014
Year: 2014

This letter describes a direct method for computing the spatially averaged outage probability of a network with interferers located according to a point process and signals subject to fading. Unlike most common approaches, it does not require transforms such as a Laplace transform. Examples show how to directly obtain the outage probability in the presence of Rayleigh fading in networks whose interferers are drawn from binomial and Poisson point processes defined over arbitrary regions. We furthermore show that, by extending the arbitrary region to the entire plane, the result for Poisson point processes converges to the same expression found by Baccelli et al..
Spatially Coupled Turbo Codes
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we introduce the concept of spatially coupled turbo codes (SC-TCs), as the turbo codes counterpart of spatially coupled low-density parity-check codes. We describe spatial coupling for both Berrou et al. and Benedetto et al. parallel and serially concatenated codes. For the binary erasure channel, we derive the exact density evolution (DE) equations of SC-TCs by using the method proposed by Kurkoski et al. to compute the decoding erasure probability of convolutional encoders. Using DE, we then analyze the asymptotic behavior of SC-TCs. We observe that the belief propagation (BP) threshold of SC-TCs improves with respect to that of the uncoupled ensemble and approaches its maximum a posteriori threshold. This phenomenon is especially significant for serially concatenated codes, whose uncoupled ensemble suffers from a poor BP threshold.
Robustness surfaces of complex networks
Venue: arXiv cs.SI 2014
Year: 2014

Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the $R^*$-value and introducing the concept of \emph{robustness surface} ($Ω$). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.
Learning cover context-free grammars from structural data
Venue: arXiv cs.FL 2014
Year: 2014

We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most $\ell.$ The goal is to learn a cover context-free grammar (CCFG) with respect to $\ell$, that is, a CFG whose structural descriptions with depth at most $\ell$ agree with those of the unknown CFG. We propose an algorithm, called $LA^\ell$, that efficiently learns a CCFG using two types of queries: structural equivalence and structural membership. We show that $LA^\ell$ runs in time polynomial in the number of states of a minimal deterministic finite cover tree automaton (DCTA) with respect to $\ell$. This number is often much smaller than the number of states of a minimum deterministic finite tree automaton for the structural descriptions of the unknown grammar.
Verification of confliction and unreachability in rule-based expert systems with model checking
Venue: arXiv cs.AI 2014
Year: 2014

It is important to find optimal solutions for structural errors in rule-based expert systems .Solutions to discovering such errors by using model checking techniques have already been proposed, but these solutions have problems such as state space explosion. In this paper, to overcome these problems, we model the rule-based systems as finite state transition systems and express confliction and unreachability as Computation Tree Logic (CTL) logic formula and then use the technique of model checking to detect confliction and unreachability in rule-based systems with the model checker UPPAAL.
DyCaPPON: Dynamic Circuit and Packet Passive Optical Network (Extended Version)
Venue: arXiv cs.NI 2014
Year: 2014

Dynamic circuits are well suited for applications that require predictable service with a constant bit rate for a prescribed period of time, such as cloud computing and e-science applications. Past research on upstream transmission in passive optical networks (PONs) has mainly considered packet-switched traffic and has focused on optimizing packet-level performance metrics, such as reducing mean delay. This study proposes and evaluates a dynamic circuit and packet PON (DyCaPPON) that provides dynamic circuits along with packet-switched service. DyCaPPON provides $(i)$ flexible packet-switched service through dynamic bandwidth allocation in periodic polling cycles, and $(ii)$ consistent circuit service by allocating each active circuit a fixed-duration upstream transmission window during each fixed-duration polling cycle. We analyze circuit-level performance metrics, including the blocking probability of dynamic circuit requests in DyCaPPON through a stochastic knapsack-based analysis. Through this analysis we also determine the bandwidth occupied by admitted circuits. The remaining bandwidth is available for packet traffic and we conduct an approximate analysis of the resulting mean delay of packet traffic. Through extensive numerical evaluations and verifying simulations we demonstrate the circuit blocking and packet delay trade-offs in DyCaPPON.
Modeling Enterprise Architecture Using Timed Colored PETRI Net: Single Processor Scheduling
Venue: arXiv cs.SE 2014
Year: 2014

The purpose of modeling enterprise architecture and analysis of it is to ease decision making about architecture of information systems. Planning is one of the most important tasks in an organization and has a major role in increasing the productivity of it. Scope of this paper is scheduling processes in the enterprise architecture. Scheduling is decision making on execution start time of processes that are used in manufacturing and service systems. Different methods and tools have been proposed for modeling enterprise architecture. Colored Petri net is extension of traditional Petri net that its modeling capability has grown dramatically. A developed model with Colored Petri net is suitable for verification of operational aspects and performance evaluation of information systems. With having ability of hierarchical modeling, colored Petri nets permits that using predesigned modules for smaller parts of the system and with a general algorithm, any kind of enterprise architecture can be modeled. A two level hierarchical model is presented as a building block for modeling architecture of Transaction Processing Systems (TPS) in this paper. This model schedules and runs processes based on a predetermined non-preemptive scheduling method. The model can be used for scheduling of processes with four non-preemptive methods named, priority based (PR), shortest job first (SJF), first come first served (FCFS) and highest response ratio next (HRRN). The presented model is designed such can be used as one of the main components in modeling any type of enterprise architecture. Most enterprise architectures can be modeled by putting together appropriate number of these modules and proper composition of them.
Enhancing User Experience for Multi-Screen Social TV Streaming over Wireless Networks
Venue: arXiv cs.MM 2014
Year: 2014

Recently, multi-screen cloud social TV is invented to transform TV into social experience. People watching the same content on social TV may come from different locations, while freely interact with each other through text, image, audio and video. This crucial virtual living-room experience adds social aspects into existing performance metrics. In this paper, we parse social TV user experience into three elements (i.e., inter-user delay, video quality of experience (QoE), and resource efficiency), and provide a joint analytical framework to enhance user experience. Specifically, we propose a cloud-based optimal playback rate allocation scheme to maximize the overall QoE while upper bounding inter-user delay. Experiment results show that our algorithm achieves near-optimal tradeoff between inter-user delay and video quality, and demonstrates resilient performance even under very fast wireless channel fading.